基于matlab的模糊图像复原

%%%%%%%%%%% 模糊图像复原的设计与实现 %%%%%%%%%%%%%%%%% %%%%%%%%%%% 1.维纳滤波算法 %%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 2.波约束最小二乘滤波算法 %%%%%%%%%%%%%%%%% %%%%%%%%%%% 3.Richardson-Lucy算法 %%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 读取原始图像 %%%%%%%%%%%%%%%%%%%%%%%%%%%% clc clear all [FileName, FilePath]=uigetfile('*.tif;*.jpg;*.png;*.img;*.gif;','请选择需要图像数据');%选择测试图片 str=[FilePath FileName];%选择图片路径地址 Ori_img = imread(str);%读取图像 figure(1) subplot(331);imshow(Ori_img);title('原始图像') %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 生成一副运动模糊图像 %%%%%%%%%%%%%%%%%%%%%% LEN = 27;THETA = 27;%设置模糊变量 psf = fspecial('motion',LEN,THETA); %点扩散函数 MoHu_img = imfilter(Ori_img,psf,'conv','circular'); % 产生运动模糊图像 subplot(332);imshow(MoHu_img);title('运动模糊图像'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 1.利用维纳滤波算法复原 %%%%%%%%%%%%%%%%%%%% %信噪比 0.01 Wiener_img_low = deconvwnr(MoHu_img,psf,0.01);%利用维纳滤波算法复原 subplot(334);imshow(Wiener_img_low);title('维纳滤波算法修复图像K=0.01'); %信噪比 0.001 Wiener_img_high = deconvwnr(MoHu_img,psf,0.001);%利用维纳滤波算法复原 subplot(335);imshow(Wiener_img_high);title('维纳滤波算法修复图像K=0.001'); %信噪比 0.0001 Wiener_img_veryhigh = deconvwnr(MoHu_img,psf,0.0001);%利用维纳滤波算法复原 subplot(335);imshow(Wiener_img_veryhigh);title('维纳滤波算法修复图像K=0.001'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 2.利用波约束最小二乘滤波算法复原 %%%%%%%% Mini_img = deconvreg(MoHu_img,psf); %利用波约束最小二乘滤波算法复原 subplot(333);imshow(Mini_img);title('约束最小二乘滤波算法修复图像'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 3.利用Richardson-Lucy算法复原 %%%%%%%%%%% %重复次数缺省10 Lucy_img_10 = deconvlucy(MoHu_img,psf); %利用Richardson-Lucy算法复原重复次数缺省 subplot(337);imshow(Lucy_img_10);title('Richardson-Lucy算法修复图像缺省'); %重复次数30 Lucy_img_30 = deconvlucy(MoHu_img,psf,30); %利用Richardson-Lucy算法复原重复次数30 subplot(338);imshow(Lucy_img_30);title('Richardson-Lucy算法修复图像30'); %重复次数60 Lucy_img_60 = deconvlucy(MoHu_img,psf,60); %利用Richardson-Lucy算法复原重复次数30 subplot(339);imshow(Lucy_img_60);title('Richardson-Lucy算法修复图像60'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 保存图像 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% imwrite(Ori_img,'测试图片保存.jpg'); imwrite(MoHu_img,'测试图片模糊.jpg'); imwrite(Wiener_img_low,'测试图片维纳0.01.jpg'); imwrite(Wiener_img_high,'测试图片维纳0.001.jpg'); imwrite(Wiener_img_veryhigh,'测试图片维纳0.0001.jpg'); imwrite(Mini_img,'测试图片最小二乘.jpg'); imwrite(Lucy_img_10,'测试图片Lucy10.jpg'); imwrite(Lucy_img_30,'测试图片Lucy30.jpg'); imwrite(Lucy_img_60,'测试图片Lucy60.jpg'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 读取每种方法处理后的效果图 %%%%%%%%%%%%%%%%% A=imread('测试图片保存.jpg');%根据选择图片名称修改 B=imread('测试图片模糊.jpg'); C=imread('测试图片维纳0.01.jpg'); D=imread('测试图片最小二乘.jpg'); E=imread('测试图片Lucy10.jpg'); F=imread('测试图片维纳0.001.jpg'); G=imread('测试图片维纳0.0001.jpg'); H=imread('测试图片Lucy30.jpg'); I=imread('测试图片Lucy60.jpg'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 计算每种方法处理后图像的峰值信噪比PSNR %%%%% psnr_Value_MuHu = PSNR(A,B); psnr_Value_WeiNa_low = PSNR(A,C); psnr_Value_WeiNa_high = PSNR(A,F); psnr_Value_WeiNa_veryhigh = PSNR(A,G); psnr_Value_Min = PSNR(A,D); psnr_Value_Lucy10 = PSNR(A,E); psnr_Value_Lucy30 = PSNR(A,H); psnr_Value_Lucy60 = PSNR(A,I); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%% 显示每种方法处理后图像的峰值信噪比PSNR %%%%% psnr_Value_MuHu%显示模糊图像信噪比 psnr_Value_WeiNa_low%显示维纳0.01信噪比 psnr_Value_WeiNa_high%显示维纳0.001信噪比 psnr_Value_WeiNa_veryhigh%显示维纳0.0001信噪比 psnr_Value_Min%显示最小二乘信噪比 psnr_Value_Lucy10%显示Lucy10信噪比 psnr_Value_Lucy30%显示Lucy30信噪比 psnr_Value_Lucy60%显示Lucy10信噪比 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%